基于Hopfield网络的柔性两轮自平衡机器人控制

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阮晓钢, 赵建伟. 基于Hopfield网络的柔性两轮自平衡机器人控制[J]. 机器人, 2010, 32(3): 405-413.. RUAN Xiaogang, ZHAO Jianwei. Flexible Two-wheeled Self-balancing Robot Control Based on Hopfield Neural Network. ROBOT, 2010, 32(3): 405-413..

摘要用弹簧模仿人的腰椎，采用LQR成功实现了机器人实物控制．针对柔性两轮自平衡机器人的姿态控制，提出了一种基于联想学习的离散Hopfield网络实现方法，以生物学习控制方式实现柔性两轮自平衡机器人在姿态控制上的自适应、自组织能力．针对非线性、强耦合的柔性机器人系统，首先定义了合理的能量变化函数，并运用柔性机器人动力学方程设计了满足该动态过程的Hopfield网络控制器，然后分析了该控制器的收敛性．仿真实验表明了该方法的有效性和系统的稳定性．对实验结果进行详细分析，表明了系统姿态控制器设计的合理性和有效性．

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关键词 ：柔性机器人, Hopfield网络, 腰椎

Abstract：Real control of robot is realized successfully by using spring to imitate the lumbar of human-being and adopt-ing LQR(linear quadratic regulator).For posture control of the flexible two-wheeled self-balancing robot,a kind of discrete Hopfield network way based on associative study is presented,and self-adaptive and self-organizing posture control is accom-plished in a manner of biological control.Firstly,a reasonable energy function is defined for the nonlinear,strong coupling and flexible robot system.Then,a Hopfield neural network controller suitable for this dynamic process is designed based on the dynamics equation of the flexible robot,and its convergence is analyzed.Simulation experiments show the effectiveness of the method and prove the stability of the system.The rationality and availability of the system posture controller design are indicated through analyzing the experiment results in detail.

Key words： flexible robot Hopfield network lumbar spine

收稿日期: 2009-05-21 录用日期: 2010-03-16

TP24

基金资助:国家863计划资助项目（2007AA04Z226）；国家自然科学基金资助项目（60774077）；北京市人才强教计划项目；高等学校博士学科点专项科研基金资助项目（63002011200601）

通讯作者: 赵建伟 E-mail: zhaojianwei@emails.bjut.edu.cn

作者简介: 阮晓钢(1958- )，男，博士后，教授．研究领域：机器人，自动控制与人工智能等．
阮晓钢(1958- )，男，博士后，教授．研究领域：机器人，自动控制与人工智能等．
赵建伟(1979- )，男，博士．研究领域：机器人，智能控制等．

链接本文:

https://robot.sia.cn/CN/ 或 https://robot.sia.cn/CN/Y2010/V32/I3/405

[1] Zhou J,Wu W,Ding B,The application of disturbance observer in two-wheeled mobile robot[C]//IEEE Conference on Robotics,Automation and Mechatronics,Piscataway,NJ,USA:IEEE,2004:171-174.
[2] 黄永志,陈卫东.两轮移动机器人运动控制系统的设计与实现[J].机器人,2004,26(1):40-44.Huang Yongzhi,Chen Weidong.Design and implementation of motion controller of two-wheeled mobile robot[a].Robot,2004,26(1):40-44.
[3] 吴克河,李为,柳长安,等.双轮驱动式移动机器人动力学控制[J].宇航学报,2006,27(2):272-275.Wu Kebe,Li Wei,Liu Changan,et al.Dynamic control of twowheeled mobile robot[J].Journal of Astronautics,2006,27(2):272-275.
[4] Boskovich S M.Two wheeled robot control system[Cl//Weseon Conference Record.Los Angeles,CA,USA:Wescon,1995:750-755.
[5] Kim D-H,Oh J-H.Tracking control of a two-wheeled mobile robot using input-output linearization[J].Control Engineering Practice,1999,7(3):369-373.

[6] Urakubo T,Tsuchiya K,Tsujita K.Motion control of a twowheeled mobile robot[J].Advanced Robotics,2001,15(7):711-728.

[7] Karniel A,Fleming K M,Sanguineti V,et al.Dynamic properties of the lamprey's neuronal circuit as it drives a two-wheeled robot[EB/OL].(2002)[2009-05-20].http://vision.technion.ac.il/karniel/pub/Kamieletal_SAB 2002.pdf.
[8] Bni T H,Nguyen T T,Chung T L,et al.A simple nonlinear control of a two-wheeled welding mobile robot[J].International Journal of Control,Automation,aad Systems,2003,1(1):35-42.
[9] Kim Y H,Kim S H,Kwak Y K.Dynamic analysis of a nonholonomic two-wheeled inverted pendulum robot[J].Journal of Intelligent and Robotic Systems:Theory and Applications,2005,44(1):25-46.

[10] Kozlowski K,Pazderski D.Stabilization of two-wheeled mobile robot using smooth control laws:Experiment study[C]//IEEE International Conference on Robotics and Automation.Piscataway,NJ,USA:IEEE,2006:3387-3392.
[11] Anderson D P.NBot Balancing Robot[EB/OL].(2010-03-01)[2010-03-02].http://www.geology.smu.edu/～dpa-www/robo/nbot/index.html.
[12] Thibodeau B J,Deegan P,Grupen R.Static analysis of contact forces with a mobile manipulator[C]//IEEE International Conference on Robotics and Automation.Piscataway,NJ,USA:IEEE,2006:4007-4012.
[13] Salerno A,Angeles J.On the nonlinear controllability of a quasiholonomic mobile robot[C]//IEEE International Conference on Robotics and Automation.Piscataway,NJ,USA:IEEE,2003:3379-3384.
[14] Grasser E D'Arrigo A,Colombi S,et al.JOE:A mobile,inverted pendulum[J].IEEE Transactions on Industrial Electronics,2002,49(1):107-114.

[15] Hopfield J J.Neural networks and physical systems with emergent collective computational abilities[J].Proceedings of the National Academy of Sciences of the United States of America:Biological Sciences,1982,79(8):2554-2558.

[16] Hopfield J J.Neurons with graded response have collective computational properties like those of two-state neurons[J].Proceedings of the National Academy of Sciences of the United States of America:Biological Sciences,1984,81(10):3088-3092.

[17] Hopfield J J,Tank D W.Neural computation of decisions in optimization problems[J].Biological Cybernetics,1985,52(3):141-152.
[18] Hopfield J J,Tank D W.Computing with neural circuits:A model[J].Science,1986,233(4764):625-633.

[19] Hopfield J J.Artificial neural networks[J].IEEE Circuits and Devices Magazine,1988,4(5):3-10.

[20] Fan C-H,Cben W-D,Xi Y-G.A neural networks-based approach to safe path planning of mobile robot in unknown environment[J].Acta Automatica Siniea,2004,30(6):816-823.
[21] Lendaris G G,Mathia K,Saeks R.Linear Hopfield networks and constrained optimization[J].IEEE Transactions on Systems,Man and Cybernetics,Part B,1999,29(1):114-118.

[22] Sadati N,Taberi J.Solving robot motion planning problem using Hopfield neural network in a fuzzified environment[C]//IEEE International Conference on Plasma Science.Piscataway,NJ,USA:IEEE,2002:1144-1149.
[23] Tani J.Visual attention and learning of a cognitive robot[C]//Lecture Notes in Computer Science,vol.1327.Berlin,Germany:Springer-Verlag,1997:697-702.
[24] Li M-A,Ruan X-G.Optimal control with continuous Hopfield neural network[C]//IEEE International Conference on Robotics,Intelligent Systems and Signal Processing.Piscataway,NJ,USA:IEEE,2003:758-762.
[25] 虞忠伟,陈辉堂,王月娟.基于Hopfield神经网络的机器人规划控制器设计[J].同济大学学报:自然科学版,2000,28(6):694-698.Yu Zhongwei,Chen Huitang,Wang Yuejuan.Robot programming controller design based on Hopfield neural network[J].Journal of Tongji University:Natural Science,2000,28(6):694-698.
[26] 姜惠兰,孙雅明.异联想记忆Hopfield神经网络的模型、算法及性能[J].系统工程理论与实践,2005,25(5):101-107.Jiang Huilan,Sun Yaming.Hetero associative memory Hopfield NN model,learning algorithms and performance[J].Systems Engineering-Theory & Practice,2005,25(5):101-107.